1. Technical Field
The present invention relates to the field of health care and, more particularly, to health care computer information systems that manage physiologic and treatment data.
2. Description of the Related Art
Most health care facilities, such as intensive care units (ICUs), acquire bedside patient information using pen and paper methodologies, such as flowsheets and patient charts. A flowsheet is a spreadsheet-type data matrix representing clinical observations over time. The paper documents used by health care facilities can include patient physiologic data, dates and times that the physiologic data was recorded, patient medications, symptoms, treatments, and clinical observations. For example, patient status information is periodically detected by bedside machines and recorded onto flowsheets by staff for a treating physician to later examine. Portions of these flowsheets can be manually entered into information systems to preserve patient information for administrative and research purposes. Further, paper documents containing physiologic data may require storage for a predefined period for record keeping purposes. Appreciably, the practice of recording and storing physiologic data on paper can be very time-consuming and expensive. Additionally, transcription errors can occur when using paper methodologies, which can result in improper treatment.
These shortcomings in managing physiologic data can be highly problematic. Physician decisions concerning patient treatments can be dependant upon the physiologic data available to the physician. The environment in which the physician works is complex, fast-paced, and is often crowded with both people and devices. Physicians can be summoned from one task to another, more urgent one, in seconds and can occasionally be required to rapidly analyze and treat patients with which the physician is only minimally familiar. In such situations, even the most accurate physiologic data can be useless to a physician if the physiologic data is presented in a confusing manner that takes concentration and time to find and comprehend. If patient data is inaccurate or misinterpreted, improper decisions can be made that can result in life altering consequences. Accordingly, the patient data upon which decisions are based should be presented in a clear, consistent, and comprehensible fashion. Further, the patient data should be available and accessible at the treatments or decision making location in order to be of use.
Another problem that exists with the conventional handling of physiologic data relates to clinical research. In order for clinical researchers to gather physiologic data, the researchers must acquire the paper documents upon which the physiologic data of patients has been recorded. The paper documents can include patient charts and flowsheets. Data from these paper documents can then be manually entered into a computing device so that the physiologic data contained within can be analyzed. This manual data entry process consumes substantial human resources and increases the likelihood of typographical errors. Further, clinical researchers will often be unaware of potentially valuable cases, since the only information sources for these cases can be paper documents, which may be difficult to search. Moreover, the paper documents from which data entry is conducted can contain confidential and/or sensitive patient information. This sensitive information can either limit the physiologic data available for clinical research purposes and/or induce additional data entry difficulties, such as requiring data entry to occur within a secure location.
One reason pen and paper methodologies have been conventionally used for recording physiologic data can relate to data integration difficulties. Presently, most physiologic data is recorded from bedside machines that monitor patients. These bedside machines generally lack the interfaces, such as an Ethernet or other network port, and/or communication standards, such a TCP/IP (Transmission Control Protocol/Internet Protocol) through which networking occurs. The only data port typically included with a bedside machine is a serial or parallel port, such as an RS-232 port. While such a data port can receive and accept data streams, these data streams follow no open standards, i.e. each bedside machine can transmit data in a proprietary manner using different data formats and protocols. In order for a computing device to communicate with a bedside machine via a data port, a tailored application must be uniquely written for that particular type of bedside machine. Present bedside machines are not packaged with software applications that facilitate communication via the data port.
A few systems do exist which can centrally present physiologic data gathered from multiple sources. These systems, however, typically exchange information in a propriety manner and can only communicate with other bedside machines which use the same proprietary protocol, i.e. other machines from a particular product line of a common manufacturer. Physiologic data from sources external to these proprietary monitoring systems, i.e. other manufacturer's bedside machines, cannot be integrated with the data contained within the proprietary monitoring systems. For example, the same type of bedside machine(e.g. a ventilator) made by a different manufacturer than the manufacturer of the proprietary monitoring system cannot be integrated with the proprietary system. Consequently, to achieve even the minimal data sharing capabilities provided by these proprietary networks, a health care provider is “locked into” a single bedside machine series or a single product line of a manufacturer. One effect of this lock-in can be a lack of a competitive marketplace resulting in higher costs and fewer monitoring options.
Presently, some systems are available to acquire data from bedside machines, however, these systems tend to utilize a proprietary physical connection and do not address unit workflow issues which is a core part to the present invention. Moreover, the presentation mechanisms for physiologic data cannot be configured so that physiologic data is presented in a manner designed to optimize physician comprehension. Further, conventional systems that monitor physiologic data do not provide mechanisms to facilitate data extraction to be used for clinical research.